Titanium dioxide surface structure exhibits water inhibition by forming distinct water–alkanol complexes.

Yong Wang’s joint appointment connects PNNL, WSU, and the next generation of scientists.

A theoretical index linking precipitation and atmospheric evaporative demand explains historical land humidity changes across observations, reanalyses, and climate models.

Observations, reanalysis, and E3SMv3 experiments linked inter-annual variability of Congo Basin surface temperature to the zonal position of precipitation over the Indo-Pacific maritime continent region.

Quasi-stationary Rossby waves shape North American temperature extremes, but higher model resolution does not always improve their modeled representation.

Tests show which low-cost 3D method best matches field measurements to minimize errors in mapping headwaters.

Watershed-based representation discretized into topographic subgrid units better captured small-scale land cover, precipitation, temperature, and snow variability across multiple spatial scales.

Numerical simulations reveal how well-controlled wall temperature and moisture can generate a stratocumulus-like cloud top in a laboratory cloud chamber.

A new tracer model tracked how May 2015 storm water re-entered the atmosphere and contributed to later rainfall.

Physics-informed and data-driven neural network models enhance Earth system models in simulating compound flooding at river-ocean interfaces.

Demonstrated that cathodic potential accelerates aqueous phase benzaldehyde hydrogenation.

Tracking water age using a new precipitation tagging method within a hydrologic model generates key information to support hydropower energy and other water-dependent systems.

Research provided definitive spectroscopic characterization, reactivity, and deactivation of a reactive monomeric diphosphine-copper hydride intermediate.

More rain and less snow shorten how long water stays in watersheds.

​​Tests show which low-cost 3D method best matches field measurements to minimize errors in mapping headwaters.​

Developed a method for selectively anchoring diverse divalent metal cations in zeolites, important for precise control over catalytic materials.

Developed a simple kinetic framework for evaluating catalyst hydride transfer ability.

PNNL has formed a partnership with the Orlando-based firm Refinity, which has licensed a key process from PNNL that will help the company convert mixed plastic waste into valuable industrial products like chemicals, plastics, and fuels.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

A low-temperature, single-stage catalytic process converts PVC and polyolefin into valuable alkanes.